Electrophoretic displays are known as promising technology for electronic paper applications and future generations of smart handheld devices, where paper-like appearance, good readability under various lighting conditions, and ultra-low power consumption are desirable. Many electrophoretic displays, such as E ink microencapsulated electrophoretic displays (MEPs), are capable of high resolution (e.g. 800×600 or above), and can be built using conventional active matrix TFT arrays that are similar to those used in LCDs, where 50 Hz (20 ms per frame) frame rate is commonly used.
However, the electro-optic characteristic of electronic ink transition states in many electrophoretic displays such as E Ink MEPs requires a minimum frame update rate of 200 Hz (5 ms per frame) in order to achieve 1 L* lightness resolution, where 1 L* represents a just noticeable difference in lightness in CIELAB (CIE 1976 L*a*b*) color space. This frame update rate is impractical for high-resolution active matrix displays nowadays. Therefore, on a 50 Hz frame rate display, previous image ghosting can appear on the screen when lightness difference larger than 1 L* occurs at pixels with the same current gray level state but different previous gray level states. FIG. 1 illustrates the lightness mismatch at two regions on an electronic ink display.
Referring to FIG. 1, the previous image is a black letter “O” with white background, and the current image is a black letter “T” with light gray background. The transitions from black to light gray and from white to light gray create a human being noticeable difference in lightness, which appears as unwanted previous image ghosting artifacts.
FIG. 2 illustrates more details of why ghosting occurs by showing the pulse width and the lightness response for different gray state transitions in an electronic display. Essentially, ghosting is a display quantization error of lightness between two transition states due to limited resolution of pulse width. As shown in FIG. 2, the width of 1 frame is the minimum unit of each pulse width, and is limited by the display frame rate (typically 50 Hz).
Ghosting is an unfavorable characteristic of electronic ink switching states in electrophoretic displays, and introduces severe imaging artifacts on the screen. To address this problem, one solution is to design optimized waveforms for the display controllers to drive the electronic state transitions. The desired impulse width is modulated by changing the sequence of driving pulses. FIG. 3 illustrates two types of waveforms from E Ink displays, direct and indirect waveforms, which are used to control the transition from dark gray to light gray on an electronic ink display. The direct waveform produces the least accuracy, i.e., worst ghosting artifacts, and the indirect waveform produces better accuracy, but requires flashiness which is also not a favorable appearance on the screen. Although the indirect waveforms can be optimized through measurements and electro-optical model prediction, there always exists a contradiction between flashiness and accuracy. Essentially, this approach is highly constrained by the impulse width resolution, which is set by the frame update rate in the pulse width modulation case described above. For more information, see Zehner, et al., “Drive Waveforms for Active Matrix Electrophoretic Displays,” Digest of Technical papers, SID Symposium, 2003, pp. 842-845, and Amundson & Sjodin, “Achieving Graytone Images in a Microencapsulated Electrophoretic Display,” Digest of Technical papers, SID Symposium, 2006, pp. 1918-1921.
It is also possible to achieve the desired impulse width by changing voltages. However, this would require more complicated display drivers that provide multiple voltages and, for these reasons, is an undesirable approach. Some different solutions exist for ghosting reduction from E Ink, all focusing on waveform tweaking with special driving pulses. For more information, see U.S. Patent Publication No. 20070080926A1, entitled “Method and Apparatus for Driving an Electrophoretic Display Device with Reduced Image Retention,” PCT Application WO2005096259A1, entitled “An Electrophoretic Display with Reduced Cross Talk,” and PCT Application WO2005050610A1, entitled “Method and Apparatus for Reducing Edge Image Retention in an Electrophoretic Display.”
Although not previously used to address the problems discussed above, there are a number of prior art image processing techniques. These include traditional halftoning, spatiotemporal dithering, and video halftoning. Traditional halftoning works for printers and displays. However, all of these traditional halftoning methods only work in the spatial dimension, and none of these methods is designed for electrophoretic displays. For more information, see M. Analoui and J. P. Allebach, “Model-Based Halftoning Using Direct Binary Search,” Proc. 1992 SPIE/IS&T Symposium on Electronic Imaging Science and Technology, Vol. 1666, San Jose, Calif., Feb. 9-14, 1992, pp. 96-108; B. Kolpatzik and C. A. Bouman, “Optimized Error Diffusion for Image Display,” J. Electronic Imaging, Vol. 69, No. 10, pp. 1340-1349, October 1979.
Spatiotemporal dithering produces high intensity resolution on display devices with low intensity resolution by diffusing the gray level quantization error into the next frame of the image for display in both spatial dimension and temporal dimension. For more information, see U.S. Pat. No. 5,254,982, entitled “Error propagated image halftoning with time-varying phase shift,” issued to Feigenblatt, et al., on Oct. 19, 1993; U.S. Pat. No. 6,714,206, entitled “Method and system for spatial-temporal dithering for displays with overlapping pixels,” issued to Martin, et al., on Mar. 30, 2004; and J. B. Mulligan, “Methods for Spatio-Temporal Dithering,” SID '93 Conference Digest, Seattle, Wash., May 17-21, 1993, pp. 155-158.
Video halftoning renders a digital video sequence onto display devices that have limited intensity resolutions and color palettes. The essential idea is to trade the spatiotemporal resolution for enhanced intensity and color resolution by diffusing the quantization error of a pixel to its spatiotemporal neighbors. This error diffusion process includes an one-dimensional temporal error diffusion and a two-dimensional spatial error diffusion, which are separable. For more information, see Z. Sun, “Video halftoning”, IEEE Transaction on Image Processing, 15(3), pp. 678-86, March, 2006; and C. B. Atkins, T. J. Flohr, D. P. Hilgenberg, C. A. Bouman, and J. P. Allebach, “Model-based color image sequence quantization,” in Proc. SPIE: Human Vision, Visual Processing, and Digital Display V, 1994, vol. 2179, pp. 310-309.